class_docstr: P2SGradLoss() MSE loss between output and target one-hot vectors
  
  See usage in __doc__ of P2SActivationLayer
class_docstr_tok: ["P2SGradLoss","(",")","MSE","loss","between","output","and","target","one-hot","vectors","See","usage","in","__doc__","of","P2SActivationLayer"]
code: def __init__(self):
      super(TrustedImplementationP2SGradLoss, self).__init__()
      self.m_loss = nn.MSELoss()
  
file_path: pytorch-metric-learning/tests/losses/test_p2s_grad_loss.py
imports: import unittest
  import torch
  import torch.nn
  from pytorch_metric_learning.losses import P2SGradLoss
  from pytorch_metric_learning.utils import common_functions
  from ..None import TEST_DEVICE, TEST_DTYPES
label_desc: Use image node_id 1 to create a new TrustedImplementationP2SGradLoss object from inherited base classes: nn with example: obj = TrustedImplementationP2SGradLoss()